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Epython Lab

Epython Lab

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Welcome to Epython Lab, where you can get resources to learn, one-on-one trainings on machine learning, business analytics, and Python, and solutions for business problems. Buy ads: https://telega.io/c/epythonlab

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You can conclude the result based on the graph shows #QuarantineYourself #LearnDataScience #Bioinformatics #Python #Pandas #M
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You can conclude the result based on the graph shows #QuarantineYourself #LearnDataScience #Bioinformatics #Python #Pandas #Matplotlib

Poll: 10 What is your plan in the upcoming 2022?
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Merry Christmas 🎄🌲🌲

Check out all #keynote

Calculating Mean Absolute Error and Mean Squared Error without using sklearn library @epythonlab #ml #AI #codetip
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Calculating Mean Absolute Error and Mean Squared Error without using sklearn library @epythonlab #ml #AI #codetip

Proper formatting names in Pandas @epythonlab #videotip #pandas

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Poll: 09 Do you think that deep learning will solve every problem?
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Telegram Shilling bots if anyone want 1. Auto search tg group and auto join 2. Silently delete tg group members msg with specific words: 3. Sending group message to discord group 4. Count users message and send winners for every 4 hours Etc 5. Many more python scripts for your telegram Msg to @asibehtenager

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TensorFlow and Scikit-learn If you're interested in solving machine learning questions, two of the most popular open-source libraries in the world for solving these problems are TensorFlow and Scikit-learn. TensorFlow and Scikit-learn, provide any data scientist the ability to use the most advanced techniques in supervised and unsupervised machine learning easily, and for a variety of situations. You can expect that TensorFlow and Scikit-learn will continue to be used for machine learning in both industry and academia for the foreseeable future. @epythonlab #keynote #tensorflow #scikitlearn

Barriers to Deep Learning Unfortunately, deep learning is not the solution to every problem. It has three major barriers: 1. It requires enough data- Deep learning requires a lot of data 2. It requires much computing power- for example:- Google's DeepMind AlphaGo required 1,202 CPUs and 176 GPUs. 3. You probably won't understand why certain decisions were being made, given the complexity and flexibility of these algorithms. Application of machine learning is one that requires deep learning. @epythonlab #keynote #deeplearning #machinelearning

Do you want to attend an introduction to Flask python based web app alive demo via Zoom on this Friday at 1:00 PM(GMT +3 time zone)? If yes, share this info for others to attend the live demo via Zoom
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Best Neural Networks and Deep Learning Books [Book] https://github.com/manjunath5496/Neural-Networks-Books @epythonlab #books
Best Neural Networks and Deep Learning Books [Book] https://github.com/manjunath5496/Neural-Networks-Books @epythonlab #books

Contact @asibehtenager if you need service
Contact @asibehtenager if you need service